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Recent developments under the term Smart Grid change how users consume electricity and interact with the power grid. Smart metering and energy management are developments that transform the yet passive energy consumer to a participant that is actively involved in the energy market by using variable energy tariffs or by demand-response services. But such functionality demands a platform that integrates all smart devices in the users property, connects to external services and electricity providers, and has interfaces that provide information and control to the user. AnyPLACE will develop such platform. Based on the latest legislation in the European member states, it will incorporate smart meters and create links to external service providers. Furthermore, it connects the devices in the property of the end-user in order to be able to fully monitor and control the energy consumption. This paper presents the AnyPLACE idea and the problems that are solved on the communications aspect. It provides an in-depth analysis of current European legislation in the context of smart metering and provides the requirements that need to be realized by the platform. Additionally, it proposes a strategy to create a solution that can be used in any place of Europe. The paper also incorporates the security and privacy requirements in different domains and sketches a solution and architecture to fulfill these by incorporating existing open source implementations as provided by the openHAB project.

Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data privacy and protection imposes the need to develop local models for flexibility modeling and forecasting and exchange models instead of personal data. This paper describes the functional architecture of an home energy management system (HEMS) and its optimization functions. A set of data-driven models, embedded in the HEMS, are discussed for improving renewable energy forecasting skill and modeling multi-period flexibility of distributed energy resources.